MCP server for semantic search with Qdrant vector database
MCP server for semantic search with Qdrant vector database. That is what the qdrant retrive mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
Options --enableHttpTransport Enable HTTP transport [default: false] --enableStdioTransport Enable stdio transport [default: true] --enableRestServer Enable REST API server [default: false] --mcpHttpPort= Port for MCP HTTP server [default: 3001] --restHttpPort= Port for REST HTTP server [default: 3002] --qdrantUrl= URL for Qdrant vector database [default: http://localhost:6333] --embeddingModelType= Type of embedding model to use [default: Xenova/all-MiniLM-L6-v2] --help Show this help message
The server publishes 8 tools. What each one is for:
qdrant_retrieve — Retrieves semantically similar documents from multiple Qdrant vector store collections based on multiple queriesInputs — - collectionNames (string[]): Names of the Qdrant collections to search acrossReturns — - results: Array of retrieved documents with:query — The query that produced this resultcollectionName — Collection name that this result came fromtext — Document text contentscore — Similarity score between 0 and 1Tools — The Tools tool exposed by this serverSetup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
Configuration is passed through the environment: QDRANT_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Plenty of database access servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Qdrant Retrive's toolset — qdrant_retrieve, Inputs, Returns and 5 more — is a fair guide to whether it matches your workflow. It is maintained by gergelyszerovay; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| qdrant_retrieve | Retrieves semantically similar documents from multiple Qdrant vector store collections based on multiple queries |
| Inputs | - collectionNames (string[]): Names of the Qdrant collections to search across |
| Returns | - results: Array of retrieved documents with: |
| query | The query that produced this result |
| collectionName | Collection name that this result came from |
| text | Document text content |
| score | Similarity score between 0 and 1 |
| Tools | The Tools tool exposed by this server. |
{
"mcpServers": {
"qdrant": {
"command": "npx",
"args": ["-y", "@gergelyszerovay/mcp-server-qdrant-retrive"],
"env": {
"QDRANT_API_KEY": "your_api_key_here"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| QDRANT_API_KEY | Credential the server authenticates with. | Yes |
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